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An attempt to formalize word sense disambiguation: maximizing efficiency by minimizing computational costs
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In: Revista española de lingüística aplicada, ISSN 0213-2028, Vol. 22, 2009, pags. 77-88 (2009)
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Bases de conocimiento multilíngües para el procesamiento semántico a gran escala ; Multilingual knowledge resources for wide–coverage semantic processing
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In: http://www.lsi.upc.edu/~nlp/meaning/documentation/3rdYear/WP6.17.pdf (2005)
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Mapping WorldNet Senses to a Lexical Database of Verbs
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In: DTIC (2001)
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Word Sense Disambiguation Using Automatically Acquired Verbal Preferences
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In: ftp://ftp.cogs.sussex.ac.uk/pub/users/dianam/senseval.ps (2000)
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H.: Semantic rule filtering for web-scale relation extraction
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In: http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
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30 |
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In: http://www.lsi.upc.edu/~nlp/meaning/documentation/2onYear/D2.2.pdf
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H.: Semantic rule filtering for web-scale relation extraction
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In: http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
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Abstract:
Abstract. Web-scale relation extraction is a means for building and extending large repositories of formalized knowledge. This type of automated knowledge building requires a decent level of precision, which is hard to achieve with automatically acquired rule sets learned from unlabeled data by means of distant or minimal supervision. This paper shows how precision of relation extraction can be considerably improved by employing a wide-coverage, general-purpose lexical semantic network, i.e., BabelNet, for effective semantic rule filtering. We apply Word Sense Disambiguation to the content words of the automatically extracted rules. As a result a set of relation-specific relevant concepts is obtained, and each of these concepts is then used to represent the structured semantics of the corresponding relation. The resulting relation-specific subgraphs of BabelNet are used as semantic filters for estimating the adequacy of the extracted rules. For the seven semantic relations tested here, the semantic filter consistently yields a higher precision at any relative recall value in the high-recall range.
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Keyword:
Relation Extraction; Rule Filtering; Semantic relations; Semantics; Web-scale; WSD
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.411.3132 http://wwwusers.di.uniroma1.it/~navigli/pubs/ISWC_2013_Moro_etal.pdf
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ABSTRACT Long Tail in Weighted Lexical Networks
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In: http://www.aclweb.org/anthology/W/W12/W12-5102.pdf
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Auto-Discovery of NVEF Word-Pairs in Chinese Abstract
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In: http://www.aclclp.org.tw/rocling/2003/M09.pdf
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World Wide Web presents several.
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In: http://www.softcomputing.net/jucs2013.pdf
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The UNED systems at SENSEVAL-2
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In: http://aclweb.org/anthology-new/S/S01/S01-1018.pdf
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ABSTRACT Long Tail in Weighted Lexical Networks
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In: http://www.lirmm.fr/~lafourcade/ML-biblio/COGALEX3/COGALEX2012-ML-v4.pdf
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USYD: WSD and Lexical Substitution using the Web1T Corpus Abstract This paper describes the University of Sydney’s WSD and Lexical Substitution systems
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In: http://www.denizyuret.com/ref/hawker/98.pdf
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Development of an Approach for Disambiguating Ambiguous Hindi postposition
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In: http://www.ijcaonline.org/volume5/number9/pxc3871317.pdf
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PARALLEL CORPORA, ALIGNMENT TECHNOLOGIES AND FURTHER PROSPECTS IN MULTILINGUAL RESOURCES AND TECHNOLOGY INFRASTRUCTURE
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In: http://www.racai.ro/~tufis/papers/Tufis-Ion-SPED2007.pdf
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Addressing Challenges in Multilingual Machine Translation
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In: http://www.ijser.org/researchpaper/Addressing_Challenges_in_Multilingual_Machine_Translation.pdf
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